Research interests

My main research focus is on applying state-of-the-art methods from digital signal processing and pattern recognition to the development of diagnostic support in various clinical fields. One strong focus in recent years has been on recognizing patterns in electroencephalograms (EEG), and scoring such data in sleep medicine. An example is the automated staging of sleep based on EEG and other biosignals such as electrooculography (EOG) and electromyography (EMG) according to international standards. We also work on novel pattern recognition techniques to extract information from those biosignals beyond visually identifiable states. Part of our work has been on using Bayesian estimation techniques to account for uncertainty in data and to arrive at most robust results. More recently my focus has also been moving toward "Data Science for Personalized Medicine".

Anderer, P. et al., 2010. Computer-Assisted Sleep Classification according to the Standard of the American Academy of Sleep Medicine: Validation Study of the AASM Version of the Somnolyzer 24 × 7. Neuropsychobiology, 62(4), pp.250-264. Available at: http://dx.doi.org/10.1159/000320864.